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regression

Papers

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Showing 4351–4375 of 9424 papers

TitleStatusHype
Beyond UCB: Optimal and Efficient Contextual Bandits with Regression Oracles—0
An Empirical Analysis of Constrained Support Vector Quantile Regression for Nonparametric Probabilistic Forecasting of Wind Power—0
Dynamic Regret for Strongly Adaptive Methods and Optimality of Online KRR—0
Dynamic Regression Discontinuity: An Event-Study Approach—0
Beyond the Norms: Detecting Prediction Errors in Regression Models—0
Dynamic programming for optimal stopping via pseudo-regression—0
Beyond Squared Error: Exploring Loss Design for Enhanced Training of Generative Flow Networks—0
An elementary analysis of ridge regression with random design—0
A divide and conquer method for symbolic regression—0
Uncertainty-Aware DNN for Multi-Modal Camera Localization—0
Dynamic Ordered Panel Logit Models—0
Dynamic optimization of volatile fatty acids to enrich biohydrogen production using a deep learning neural network—0
Dynamic Multivariate Functional Data Modeling via Sparse Subspace Learning—0
An Efficient Pseudo-likelihood Method for Sparse Binary Pairwise Markov Network Estimation—0
Dynamic Heterogeneous Distribution Regression Panel Models, with an Application to Labor Income Processes—0
Beyond Ridge Regression for Distribution-Free Data—0
Dynamic Exploration-Exploitation Trade-Off in Active Learning Regression with Bayesian Hierarchical Modeling—0
Dynamic covariate balancing: estimating treatment effects over time with potential local projections—0
An Efficient Pruning Algorithm for Robust Isotonic Regression—0
A distribution-free mixed-integer optimization approach to hierarchical modelling of clustered and longitudinal data—0
Dynamic Attention-controlled Cascaded Shape Regression Exploiting Training Data Augmentation and Fuzzy-set Sample Weighting—0
Beyond Log-Concavity: Theory and Algorithm for Sum-Log-Concave Optimization—0
Dynamical System Identification, Model Selection and Model Uncertainty Quantification by Bayesian Inference—0
Dyadic Regression with Sample Selection—0
Beyond linear regression: mapping models in cognitive neuroscience should align with research goals—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Neural NetworkR2 Score0.79—Unverified
2Baseline RegressionR2 Score0.58—Unverified
3Mimic / SurrogateR2 Score0.57—Unverified
#ModelMetricClaimedVerifiedStatus
1Neural NetworkR2 Score0.86—Unverified
2Baseline RegressionR2 Score0.59—Unverified
3Mimic / SurrogateR2 Score0.58—Unverified
#ModelMetricClaimedVerifiedStatus
1Neural NetworkR2 Score0.87—Unverified
2Baseline RegressionR2 Score0.78—Unverified
3Mimic / SurrogateR2 Score0.78—Unverified
#ModelMetricClaimedVerifiedStatus
1Neural NetworkR2 Score0.98—Unverified
2Baseline RegressionR2 Score-0.01—Unverified
3Mimic / SurrogateR2 Score-0.01—Unverified
#ModelMetricClaimedVerifiedStatus
1XGBoost-MACCSmicro-averaged RMSE0.93—Unverified
2RF-ToxPrintchemical macro-average RMSE0.85—Unverified
#ModelMetricClaimedVerifiedStatus
1Linear and Decision Tree RegressionR Squared86.84—Unverified